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How the AI-assisted discovery and synthesis of a ternary oxide highlights capability gaps in materials science

Joseph H. Montoya, Carolyn Grimley, Muratahan Aykol, Colin Ophus, Hadas Sternlicht, Benjamin H. Savitzky, Andrew M. Minor, Steven B. Torrisi, Jackson Goedjen, Ching‐Chang Chung, Andrew H. Comstock, Shijing Sun

2024Chemical Science18 citationsDOIOpen Access PDF

Abstract

hot-stage X-ray diffraction in order to realize new ternary oxide phases experimentally. We applied this strategy in six ternary transition-metal oxide chemistries previously considered well-explored, one of which culminated in the discovery of two novel phases of calcium ruthenates. Detailed characterization using room temperature X-ray powder diffraction, 4D-STEM and SQUID measurements identifies the structure and composition and confirms distinct properties, including distinct defect concentrations, of one of the new phases formed in our experimental campaigns. While the discovery of a new material guided by AI and DFT theory represents a milestone, our procedure and results also highlight a number of critical gaps in the process that can inform future efforts towards the improvement of AI-coupled methodologies.

Topics & Concepts

Ternary operationNanotechnologyMaterials scienceOxideCombinatorial chemistryChemistryComputer scienceMetallurgyProgramming languageMachine Learning in Materials ScienceElectronic and Structural Properties of OxidesCatalysis and Oxidation Reactions
How the AI-assisted discovery and synthesis of a ternary oxide highlights capability gaps in materials science | Litcius